CN107357293A - Method for planning path for mobile robot and system - Google Patents

Method for planning path for mobile robot and system Download PDF

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Publication number
CN107357293A
CN107357293A CN201710643674.7A CN201710643674A CN107357293A CN 107357293 A CN107357293 A CN 107357293A CN 201710643674 A CN201710643674 A CN 201710643674A CN 107357293 A CN107357293 A CN 107357293A
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mobile robot
path
map
repulsion
east
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丁肇红
任志伟
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Shanghai Institute of Technology
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Shanghai Institute of Technology
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors

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  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
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  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
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Abstract

The invention provides a kind of method for planning path for mobile robot and system, including：Map is established according to the traveling environmental data of mobile robot；It is multiple uniform grids by map partitioning, obtains initial map, determines start position and final position of the mobile robot on initial map；Receive the obstacle signal that the sensor in mobile robot detects；According to obstacle signal, mobile robot repulsion suffered on current location is determined；According to the repulsion field of the decay of mobile robot repulsion structure barrier region suffered on current location；Assignment is carried out to each grid in initial map according to the repulsion field of decay, obtains the grating map after assignment；And travel path of the mobile robot towards final position is generated using non-traversal search mode.The present invention is not related to the Vector operation of potential field power when planning optimal path completely, eliminates the possibility for the local best points " deadlock " that Artificial Potential Field Method may occur.

Description

Method for planning path for mobile robot and system
Technical field
The present invention relates to mobile robot technology field, in particular it relates to method for planning path for mobile robot and system.
Background technology
Mobile robot is that one kind can be by sensor senses environment and oneself state, the real environment now with barrier In object-oriented paleocinetic system.Because mobile robot may pass through various obstacles when going to objective Thing, it is therefore desirable to plan the travel path of mobile robot.
At present, include in all multi-methods of the path planning of mobile robot：Artificial Potential Field Method and grating map method.But It is that Artificial Potential Field Method is easily trapped into local minimum point, so as to cause mobile robot to reach target location.Traditional grid The basic part of lattice Map Method is minimum grid scale, and map is carried out into grid division with this.Grating map method can be compared with For convenience try to achieve the collisionless path that any two passes through between grid using recursive algorithm, but need larger resource and reality Trample, and path optimization's degree is undesirable.
Therefore, the method efficiency at present on the path planning of mobile robot is low, can not fundamentally avoid artificial gesture Local minimum points " deadlock " problem of field method.
The content of the invention
For in the prior art the defects of, it is an object of the invention to provide a kind of method for planning path for mobile robot and be System.
According to method for planning path for mobile robot provided by the invention, including：
Map is established according to the traveling environmental data of mobile robot；
It is multiple uniform grids by the map partitioning, obtains initial map, wherein, the initial map In each grid correspond to initial matrix in corresponding one can assignment element；
Determine start position and final position of the mobile robot on the initial map；
Receive the obstacle signal that the sensor in the mobile robot detects；
According to the obstacle signal, mobile robot repulsion suffered on current location is determined；
According to the repulsion field of the decay of mobile robot repulsion structure barrier region suffered on current location；
Assignment is carried out to each grid in the initial map according to the repulsion field of the decay, after obtaining assignment Grating map；
According to the grating map after the assignment, the mobile robot is generated towards terminal using non-traversal search mode The travel path of position, wherein, the non-traversal search mode refers to：Determine that mobile robot exists according to default search order It whether there is barrier on the path of all directions in the range of the setting search radius of current location, when it is determined that nothing in either direction During barrier, then advance towards the direction.
Alternatively, it is described according to the obstacle signal, determine mobile robot reprimand suffered on current location Power, including：
The obstacle signal according to receiving determines the distance between barrier and the mobile robot and barrier Hinder the scope of object area.
Alternatively, the repulsion suffered on current location according to the mobile robot builds declining for barrier region The repulsion field subtracted, including：
Center using barrier region as repulsion field, the decay repulsion field of the barrier region is built by G-function, Wherein described G-function is as follows：
G is gravitation Gravitation abbreviation, and functional expression is as follows
In formula：ξ is gravitation potential field constant,WithThe distance of robot and target point is represented respectively.
Alternatively, the grating map based on after the assignment, the moving machine is generated according to non-traversal search mode Device people towards final position travel path, including：
Assuming that the coordinate of the start position of the mobile robot is：(Xs, Ys), the coordinate in final position is：(Xf, Yf)； Based on Sugeno fuzzy models, determine that the search order of non-traversal search mode is as follows：
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from west to north, by north to east, by east to south Scan for；
In Xs＞ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from north to east, by east to south, by south to east Scan for；
In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from east to north, by north to west, by west to south Scan for；
In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from north to east, by east to south, by south to west Scan for；
In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from east to south, by south to west, by west to north Scan for；
In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from south to east, by east to north, by north to west Scan for；
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from west to south, by south to east, by east to north Scan for；
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from south to west, by west to east, by east to north Scan for.
Alternatively, the grating map based on after the assignment, the moving machine is generated according to non-traversal search mode Device people towards final position travel path, including：
The priority orders of the direction of search under the mobile robot current location are determined according to final position；
First search is towards whether there is barrier on the direction in final position, if the direction in final position has obstacle Thing, then sequentially searched for according to the priority orders in remaining direction.
Alternatively, when multiple barriers be present, the assignment of each grid in the initial map also needs to fold A barrier is added for gravitation caused by the gonglion of the grid and/or repulsion value.
Alternatively, in addition to：When barrier be present around the mobile robot current location, type merging has been carried out Operation, specifically：
Assuming that during the value of diagonal two FOHs of search, two diagonal colleague areas are impassabitity region, then really Whether the region of set field covering is less than default barrier zone and merges threshold value SPsquare；If the region of potential field covering is less than default Barrier zone merge threshold value SPsquare, then gestalt union operation is carried out to barrier zone.
Alternatively, in addition to：
Path point of the mobile robot on the grating map after the assignment is detected, wherein, the path point is The central point for the grid that the mobile robot mobile route is passed through；
Judge whether the path that continuous N path point is formed is knuckle path；M is the integer more than 1；
Continuous N path point form path be knuckle path when, then by the drop shadow spread of the mobile robot extremely On knuckle path, when the drop shadow spread of the mobile robot is less than knuckle path width, shown knuckle path is converted into Straight line path.
According to mobile robot path planning system provided by the invention, including：
Map generation module, map is established for the traveling environmental data according to mobile robot；
Initial map generation module, for being multiple uniform grids by the map partitioning, obtain initial Map, wherein, each grid in the initial map corresponds in initial matrix corresponding one can assignment Element；
First determining module, for determining start position and end of the mobile robot on the initial map Point position；
Receiving module, the obstacle signal detected for receiving the sensor in the mobile robot；
Second determining module, for according to the obstacle signal, determining mobile robot institute on current location The repulsion received；
Repulsion field builds module, for building barrier according to mobile robot repulsion suffered on current location The repulsion field of the decay in region；
Assignment map generation module, for the repulsion field according to the decay to each grid in the initial map Lattice carry out assignment, obtain the grating map after assignment；
Path-generating module, for according to the grating map after the assignment, being generated using non-traversal search mode described Mobile robot towards final position travel path, wherein, the non-traversal search mode refers to：It is suitable according to default search Sequence determines that mobile robot whether there is barrier in the range of the setting search radius of current location on the path of all directions, When it is determined that during clear in either direction, then advancing towards the direction.
Compared with prior art, the present invention has following beneficial effect：
Method for planning path for mobile robot provided by the invention, by possessed by each grid in grating map Be superimposed complete potential field force value, and searching algorithm by meet trend guiding in a manner of come control travel direction towards setting eventually Point.It is not related to the Vector operation of force field during due to path planning completely, fundamentally avoids the part of article market method most Dot " deadlock " problem.It is not related to the Vector operation of potential field power completely when planning optimal path, eliminates Artificial Potential Field The possibility for the local best points " deadlock " that method may occur.And the thought and grating map of Sugeno fuzzy models are merged The advantages of algorithm, Artificial Potential Field, the problem of can not only avoiding " local minimum points are locked ", and algorithm can also be caused to calculate During data operation quantity reduce.The advantages of with the primary system plan, had a distinct increment in reliability, security, efficiency.
Brief description of the drawings
The detailed description made by reading with reference to the following drawings to non-limiting example, further feature of the invention, Objects and advantages will become more apparent upon：
Fig. 1 is the schematic flow sheet for the method for planning path for mobile robot that the embodiment of the present invention one provides；
Fig. 2 is the grating map schematic diagram for the method for planning path for mobile robot that the embodiment of the present invention two provides；
Fig. 3 is the grating map schematic diagram for the method for planning path for mobile robot that the embodiment of the present invention three provides；
Fig. 4 is the complete type result schematic diagram in special obstacle region；
Fig. 5 is the route programming result schematic diagram being not optimised；
Fig. 6 is the route programming result schematic diagram of optimization；
Fig. 7 is the boot parameter schematic diagram in 12 directions.
Embodiment
With reference to specific embodiment, the present invention is described in detail.Following examples will be helpful to the technology of this area Personnel further understand the present invention, but the invention is not limited in any way.It should be pointed out that the ordinary skill to this area For personnel, without departing from the inventive concept of the premise, some changes and improvements can also be made.These belong to the present invention Protection domain.
According to method for planning path for mobile robot provided by the invention, including：According to the traveling environment of mobile robot Data establish map；It is multiple uniform grids by map partitioning, obtains initial map, wherein, in initial map Each grid correspond to initial matrix in corresponding one can assignment element；Determine mobile robot in initial Start position and final position on map；Receive the obstacle signal that the sensor in mobile robot detects；According to barrier Hinder thing signal, determine mobile robot repulsion suffered on current location；According to mobile robot on current location suffered by Repulsion structure barrier region decay repulsion field；According to the repulsion field of decay to each grid in initial map Assignment is carried out, obtains the grating map after assignment；According to the grating map after assignment, movement is generated using non-traversal search mode Robot towards final position travel path, wherein, non-traversal search mode refers to：Determine to move according to default search order Mobile robot whether there is barrier in the range of the setting search radius of current location on the path of all directions, when it is determined that appointing On one direction during clear, then direction advances.
According to obstacle signal, mobile robot repulsion suffered on current location is determined, including：According to what is received Obstacle signal determines the scope of the distance between barrier and mobile robot and barrier region.According to mobile robot The repulsion field of the decay of suffered repulsion structure barrier region on current location, including：Using barrier region as repulsion The center of field, the decay repulsion field of barrier region is built by G-function, and wherein G-function is as follows：
G is gravitation Gravitation abbreviation, and functional expression is as follows
In formula：ξ is gravitation potential field constant,WithThe distance of robot and target point is represented respectively.
Based on the grating map after assignment, row of the mobile robot towards final position is generated according to non-traversal search mode Inbound path, including：Assuming that the coordinate of the start position of mobile robot is：(Xs, Ys), the coordinate in final position is：(Xf, Yf)； Based on Sugeno fuzzy models, determine that the search order of non-traversal search mode is as follows：
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from west to north, by north to east, by east to south Scan for；
In Xs＞ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from north to east, by east to south, by south to east Scan for；
In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from east to north, by north to west, by west to south Scan for；
In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from north to east, by east to south, by south to west Scan for；
In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from east to south, by south to west, by west to north Scan for；
In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from south to east, by east to north, by north to west Scan for；
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, according to the direction from west to south, by south to east, by east to north Scan for；
In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, according to the direction from south to west, by west to east, by east to north Scan for.
Based on the grating map after assignment, row of the mobile robot towards final position is generated according to non-traversal search mode Inbound path, including：The priority orders of the direction of search under mobile robot current location are determined according to final position；Preferentially search It whether there is barrier on the direction in Suo Chaoxiang final positions, if the direction in final position has barrier, according to residue side To priority orders sequentially searched for.
When multiple barriers be present, the assignment of each grid in initial map also needs to be superimposed multiple barriers For gravitation caused by the gonglion of grid and/or repulsion value.
When barrier be present around mobile robot current location, type union operation is carried out, specifically：
Assuming that during the value of diagonal two FOHs of search, diagonal two colleague areas are impassabitity region, it is determined that gesture Whether the region of field covering is less than default barrier zone and merges threshold value SPsquare；If the region of potential field covering is less than default barrier Hinder region merging technique threshold value SPsquare, then gestalt union operation is carried out to barrier zone.
Path point of the mobile robot on the grating map after assignment is detected, wherein, path point is moved for mobile robot The central point for the grid that dynamic path is passed through；Judge whether the path that continuous N path point is formed is knuckle path；M is more than 1 Integer；Continuous N path point form path be knuckle path when, then by the drop shadow spread of mobile robot to knuckle road On footpath, when the drop shadow spread of mobile robot is less than knuckle path width, shown knuckle path is converted into straight line path.
According to mobile robot path planning system provided by the invention, including：Map generation module, for according to movement The traveling environmental data of robot establishes map；Initial map generation module, for being multiple uniform by map partitioning Grid, initial map is obtained, wherein, each grid in initial map corresponds to corresponding in initial matrix One can assignment element；First determining module, for determine start position of the mobile robot on initial map and Final position；Receiving module, the obstacle signal that the sensor for receiving in mobile robot detects；Second determines mould Block, for according to obstacle signal, determining mobile robot repulsion suffered on current location；Repulsion field builds module, uses In the repulsion field for the decay that barrier region is built according to mobile robot repulsion suffered on current location；Assignment map is given birth to Into module, assignment is carried out to each grid in initial map for the repulsion field according to decay, obtains the grid after assignment Lattice map；Path-generating module, for according to the grating map after assignment, mobile robot to be generated using non-traversal search mode Towards the travel path in final position, wherein, non-traversal search mode refers to：Mobile machine is determined according to default search order People whether there is barrier in the range of the setting search radius of current location on the path of all directions, when it is determined that either direction During upper clear, then direction advances.
With regard to no longer carrying out potential field after generating completion and calculating barrier repulsion field in grating map constructed by the present invention The Vector operation of power, but by the potential field force value of superimposed completion possessed by each grid in grating map, and pass through Search meet trend guiding mode come control travel direction towards setting terminal.Due to not being related to force completely during path planning The Vector operation of field, fundamentally avoid local minimum points " deadlock " problem of Artificial Potential Field Method.
Specifically, the characteristics of being linearized using the dimmed model segments of Sugeno, can use with reference to the thought of Artificial Potential Field Non- traversal search mode, search radius are four grids.
Below for convenience of illustrating, search radius is two grids.In fig. 2, each small grid GiIt is upper (i=1,2 ..., 25) position of grid is represented, the numerical value of lower section represents the reprimand planned according to the thought of Artificial Potential Field Method by G-function for barrier The field of force.In FIG. 2, it is assumed that mobile robot is currently at point G13, then first by search for its direct neighbor G12, G14, G8, G18 four direction.Direction was searched according to each path planning time different set Origin And Destination, according to setting starting point (Xs, Ys) arrive terminal (Xf, Yf) coordinate relative position generation monitoring direction and priority and assign weight, Wdirectiong[i]；i =0,1,2,3 is priority weight coefficient.Following eight kinds of search orders are summed up with reference to Sugeno fuzzy model thoughts：
①if:Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf|
then:W→N→E→S
②if:Xs＞ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf|
then:N→W→S→E
③if:Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＞ | YS-Yf|
then:E→N→W→S
④if:Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf|
then:N→E→S→W
⑤if:Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf|
then:E→S→W→N
⑥if:Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf|
then:S→E→N→W
⑦if:Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf|
then:W→S→E→N
⑧if:Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf|
then:S→W→E→N
In formula：S represents southern to W represents west to E represents east to N represents the north to → expression direction conversion.
Further, if Fig. 3 E of the setting terminal in G13 points is assumed, S directions (southeastern direction) and on final position X-direction on absolute distance it is longer, then planning algorithm will be searched for successively according to the priority orders from G14, G18, G12, G8.Then First Searching point is G14.Cumulative 7 remaining direction points (G9, G15, G19, G8, G10, G18, G20) centered on G14 points Repulsion field sum, be designated as SumpointN, and it is multiplied by the priority weight coefficient W of the directiondirectiong[0], then the direction of the point is drawn The calculation formula for leading parameter is as follows：
GGuiding factou Point 13-14=Sumpoint 13-14*Wdirectionorg[0]
In formula：GGuiding factou Point 13-14Represent 13-14 boot parameter, Sumpoint13-14Represent centered on 13 points (not including 13 points) 7 remaining direction points repulsion potential field value sum, Wdirectionorg[0] represent the point in correspondence direction Priority weight coefficient.
Similarly：G18 direction boot parameter is：
GGuiding factou Point 13-18=Sumpoint13-18*Wdirectionorg[1]
In formula：GGuiding factou Point 13-18Represent 13-18 boot parameter, Sumpoint 13-18During expression is with 13 points The sum of the repulsion potential field value of (not including 13 points) 7 remaining direction points of the heart, Wdirectionorg[1] represent the point in counterparty To priority weight coefficient.
G12 direction boot parameter is：
GGuiding factou Point 13-12=Sumpoint 13-12*Wdirectionorg[2]
In formula：GGuiding factou Point 13-12Represent 13-12 boot parameter, Sumpoint13-12Represent centered on 13 points (not including 13 points) 7 remaining direction points repulsion potential field value sum, Wdirectionorg[2] represent the point in correspondence direction Priority weight coefficient.
The direction boot parameter of G8 points is：
GGuiding factou Point 13-8=Sumpoint 13-8*Wdirectionorg[3]
In formula：GGuiding factou Point 13-8Represent 13-8 boot parameter, Sumpoint13-8Represent centered on 13 points The sum of the repulsion potential field value of (not including 13 points) 7 remaining direction points, Wdirectionorg[3] represent the point in correspondence direction Priority weight coefficient.
Because assuming that search radius is 2, then need to scan for the peripheral direction of first layer point, as shown in figure 4, with right G14 point peripheral directions (are free of exemplified by scanning for and derive point G13).
If the direction boot parameter for calculating 13-14-9 is
Gguiding factor Point 13-14-9=Sumpoint13-14-9*Wdirectionorg[3]
In formula：Gguiding factor Point 13-14-9Represent 13-14-9 boot parameter, Sumpoint13-14-9Represent represent with The sum of the repulsion potential field value of (not including 13 points) 7 remaining direction points centered on 13 points, Wdirectionorg[3] point is represented In the priority weight coefficient of correspondence direction.
The guiding that 12 directions in the range of G13 points periphery R=2 (grid is 2 path length) are obtained by this circulation is joined Number.G as shown in Figure 7guiding foctor PointM-N-I is abbreviated as GM-N-I, then 12 centered on M direction boot parameters include： GM-N-I,GM-N-O、GM-N-S、GM-R-S、GM-R-W、GM-R-Q、GM-L-Q、GM-L-K、GM-L-G、GM-H-G、GM-H-C、 GM-H-I.And the boot parameter deposit data link table in 12 directions is retrieved into minimum value therein, setting first for backtracking reference Layer point is path point, and using the path point as new central point, above-mentioned algorithm is repeated, until eventually finding target point.If go out The equal situation of existing value, then select the minimum point of motion platform postural change path point all the way under.
When there is situation as shown in Figure 4, when being searched for due to mobile robot in red framework, its sensor feedback four All environment obtain barrier zone, merge threshold values SP when the framework region for attempting covering is less than setting barrier zonerectWhen, so should Such barrier zone is finished into type union operation.
Because the basis of path planning is grating map, on the premise of core path planning algorithm is Artificial Potential Field, rule The arc path marked becomes constantly knuckle on the contrary, the covert hardware cumulative errors increase caused by the path.To be excellent Change problems, such as：By using three, four, five path points by one group formed special knuckle shape template (totally four Kind) the whole critical path point queue of traversal search ordered path queue stored before generating, knuckle shape template is converted into Corresponding cut-off template of cut-offfing.But directly apply mechanically template connection angle steel joint and be likely to result in mobile robot in critical traveling When, there is barrier in its volume, therefore need to be verified.
Checking procedure is optimizes drawn critical path queue by last, by robot vertical projected area CAbsolute fieldThe path is projected to, that is, generates complete trails safe range, as shown in Figure 6 (note：In example for convenience of description, if CAbsolute fieldSize is a grid, then snakelike grid area coverage is complete trails safe range), raster path is crucial Found in the real effect of optimization of turning point, if retain the part of broken line connects angle steel joint its line not in snakelike grid according to template In the complete trails safe range of lattice covering, therefore retain knuckle.
It should be noted that the step in method for planning path for mobile robot provided by the invention, can utilize movement Corresponding module, device, unit etc. are achieved in robot path planning's system, and those skilled in the art are referred to system Technical scheme implementation method step flow, i.e. the embodiment in system can be regarded as the preference of implementation method, herein not Give and repeating.
One skilled in the art will appreciate that except realizing system provided by the invention in a manner of pure computer readable program code And its beyond each device, completely can by by method and step carry out programming in logic come system provided by the invention and its Each device is in the form of gate, switch, application specific integrated circuit, programmable logic controller (PLC) and embedded microcontroller etc. To realize identical function.So system provided by the invention and its every device are considered a kind of hardware component, and it is right What is included in it is used to realize that the device of various functions can also to be considered as the structure in hardware component；It will can also be used to realize respectively The device of kind of function, which is considered as, not only can be the software module of implementation method but also can be the structure in hardware component.
The specific embodiment of the present invention is described above.It is to be appreciated that the invention is not limited in above-mentioned Particular implementation, those skilled in the art can make a variety of changes or change within the scope of the claims, this not shadow Ring the substantive content of the present invention.In the case where not conflicting, the feature in embodiments herein and embodiment can any phase Mutually combination.

Claims (9)

  1. A kind of 1. method for planning path for mobile robot, it is characterised in that including：
    Map is established according to the traveling environmental data of mobile robot；
    It is multiple uniform grids by the map partitioning, obtains initial map, wherein, in the initial map Each grid correspond in initial matrix corresponding one can assignment element；
    Determine start position and final position of the mobile robot on the initial map；
    Receive the obstacle signal that the sensor in the mobile robot detects；
    According to the obstacle signal, mobile robot repulsion suffered on current location is determined；
    According to the repulsion field of the decay of mobile robot repulsion structure barrier region suffered on current location；
    Assignment is carried out to each grid in the initial map according to the repulsion field of the decay, obtains the grid after assignment Lattice map；
    According to the grating map after the assignment, the mobile robot is generated towards final position using non-traversal search mode Travel path, wherein, the non-traversal search mode refers to：Determine mobile robot current according to default search order Whether there is barrier on the path of all directions in the range of the setting search radius of position, when it is determined that in either direction it is accessible During thing, then advance towards the direction.
  2. 2. method for planning path for mobile robot according to claim 1, it is characterised in that described according to the barrier Signal, mobile robot repulsion suffered on current location is determined, including：
    The obstacle signal according to receiving determines the distance between barrier and the mobile robot and barrier The scope in region.
  3. 3. method for planning path for mobile robot according to claim 1, it is characterised in that described according to the moving machine The repulsion field of the decay of device people repulsion structure barrier region suffered on current location, including：
    Center using barrier region as repulsion field, the decay repulsion field of the barrier region is built by G-function, wherein The G-function is as follows：
    G is gravitation Gravitation abbreviation, and functional expression is as follows
    <mrow> <mover> <msub> <mi>U</mi> <mrow> <mi>a</mi> <mi>t</mi> </mrow> </msub> <mo>&amp;RightArrow;</mo> </mover> <mrow> <mo>(</mo> <mover> <mi>q</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <mi>&amp;xi;</mi> <msup> <mrow> <mo>(</mo> <mrow> <mover> <mi>q</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>,</mo> <mover> <msub> <mi>q</mi> <mrow> <mi>g</mi> <mi>o</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>&amp;RightArrow;</mo> </mover> </mrow> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow>
    In formula：ξ is gravitation potential field constant,WithThe distance of robot and target point is represented respectively.
  4. 4. method for planning path for mobile robot according to claim 1, it is characterised in that described based on after the assignment Grating map, travel path of the mobile robot towards final position is generated according to non-traversal search mode, including：
    Assuming that the coordinate of the start position of the mobile robot is：(Xs, Ys), the coordinate in final position is：(Xf, Yf)；It is based on Sugeno fuzzy models, determine that the search order of non-traversal search mode is as follows：
    In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, carried out according to from west to north, by north to east, by the direction in east to south Search；
    In Xs＞ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, carried out according to from north to east, by east to south, by the direction in south to east Search；
    In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＞ | YS-Yf| when, carried out according to from east to north, by north to west, by the direction in west to south Search；
    In Xs＜ Xf,Ys＞ Yf,|Xs-Xf| ＜ | YS-Yf| when, carried out according to from north to east, by east to south, by the direction in south to west Search；
    In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, carried out according to from east to south, by south to west, by the direction in west to north Search；
    In Xs＜ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, carried out according to from south to east, by east to north, by the direction in north to west Search；
    In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＞ | YS-Yf| when, carried out according to from west to south, by south to east, by the direction in east to north Search；
    In Xs＞ Xf,Ys＜ Yf,|Xs-Xf| ＜ | YS-Yf| when, carried out according to from south to west, by west to east, by the direction in east to north Search.
  5. 5. method for planning path for mobile robot according to claim 1, it is characterised in that described based on after the assignment Grating map, travel path of the mobile robot towards final position is generated according to non-traversal search mode, including：
    The priority orders of the direction of search under the mobile robot current location are determined according to final position；
    First search is towards whether there is barrier on the direction in final position, if barrier be present in the direction in final position, Sequentially searched for according to the priority orders in remaining direction.
  6. 6. according to the method for planning path for mobile robot described in any one in claim 1-5, it is characterised in that exist During multiple barriers, the assignment of each grid in the initial map also needs to be superimposed multiple barriers for the grid Gravitation caused by center of a lattice focus and/or repulsion value.
  7. 7. according to the method for planning path for mobile robot described in any one in claim 1-5, it is characterised in that also wrap Include：When barrier be present around the mobile robot current location, type union operation is carried out, specifically：
    Assuming that during the value of diagonal two FOHs of search, two diagonal colleague areas are impassabitity region, it is determined that gesture Whether the region of field covering is less than default barrier zone and merges threshold value SPsquare；If the region of potential field covering is less than default barrier Hinder region merging technique threshold value SPsquare, then gestalt union operation is carried out to barrier zone.
  8. 8. according to the method for planning path for mobile robot described in any one in claim 1-5, it is characterised in that also wrap Include：
    Path point of the mobile robot on the grating map after the assignment is detected, wherein, the path point is described The central point for the grid that mobile robot mobile route is passed through；
    Judge whether the path that continuous N path point is formed is knuckle path；M is the integer more than 1；
    Continuous N path point form path be knuckle path when, then by the drop shadow spread of the mobile robot to knuckle On path, when the drop shadow spread of the mobile robot is less than knuckle path width, shown knuckle path is converted into straight line Path.
  9. A kind of 9. mobile robot path planning system, it is characterised in that including：
    Map generation module, map is established for the traveling environmental data according to mobile robot；
    Initial map generation module, for being multiple uniform grids by the map partitioning, initial map is obtained, Wherein, each grid in the initial map correspond to initial matrix in corresponding one can assignment element；
    First determining module, for determining start position and terminal position of the mobile robot on the initial map Put；
    Receiving module, the obstacle signal detected for receiving the sensor in the mobile robot；
    Second determining module, for according to the obstacle signal, determine the mobile robot on current location it is suffered Repulsion；
    Repulsion field builds module, for building barrier region according to mobile robot repulsion suffered on current location Decay repulsion field；
    Assignment map generation module, each grid in the initial map is entered for the repulsion field according to the decay Row assignment, obtain the grating map after assignment；
    Path-generating module, for according to the grating map after the assignment, the movement to be generated using non-traversal search mode Robot towards final position travel path, wherein, the non-traversal search mode refers to：It is true according to default search order Determine mobile robot and whether there is barrier on the path of all directions in the range of the setting search radius of current location, when true When determining clear in either direction, then advance towards the direction.
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